Smartphone applications are emerging as popular media for promoting one’s products through in-app advertisements. Today, there are a number of organizations, known as supply-side-platforms (SSP), who aggregate and auction these ad-spaces from different suppliers/publishers. Advertisers (or their intermediaries) place bid for these spaces based on different relevance criteria (e.g., the location and device of the app-user, the app’s IAB category etc.), the impression value, clickthrough value, and the conversion value. After the received ads are filtered based on relevance, the SSP is often still faced with a number of options for ad-placement, each having different revenues owing to differences in clickthrough rates etc. Moreover, the SSP has to decide on the ad-placement in real-time. In this paper, we consider the SSP’s ad-placement problem in the aforementioned situation. We propose an optimization model to maximize the SSP’s revenues. Based on computational experience with this model, we develop a rule-based online algorithm that appears to be viable as a real-time solution.